Results 271 to 280 of about 24,206 (303)

On multivariate smoothed bootstrap consistency

Journal of Statistical Planning and Inference, 2008
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
DE MARTINI D, RAPALLO F
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Importance resampling for the smoothed bootstrap

Journal of Statistical Computation and Simulation, 1992
Alternative methods of estimating properties of unknown distributions include the bootstrap and the smoothed bootstrap. In the standard bootstrap setting, Johns (1988) introduced an importance resam¬pling procedure that results in more accurate approximation to the bootstrap estimate of a distribution function or a quantile.
Zehua Chen, Kim-Anh Do
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Efficient construction of a smooth nonparametric family of empirical distributions and calculation of bootstrap likelihood [PDF]

Computational Statistics, 2011
This paper considers the efficient construction of a nonparametric family of distributions indexed by a specified parameter of interest and its application to calculating a bootstrap likelihood for the parameter. An approximate expression is obtained for
Bruce J. Worton, Worton, Bruce
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Optimizing the smoothed bootstrap

Annals of the Institute of Statistical Mathematics, 1995
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On Bootstrapping Using Smoothed Bootstrap

2019
The standard bootstrap method was introduced as a resampling method for statistical inference; it is a computer based method for assigning measures of accuracy to statistical estimates. The bootstrap sample is obtained by randomly sampling n times, with replacement, from the original sample.
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Smoothed Empirical Processes and the Bootstrap

2003
Based on a uniform functional central limit theorem (FCLT) for unbiased smoothed empirical processes indexed by a class.F of measurable functions defined on a linear metric space we present a consistency theorem for smoothed bootstrapped empirical processes.
Peter Gaenssler, Daniel Rost
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Bootstrapping the distance between smooth bootstrap and sample quantile distribution

Probability Theory and Related Fields, 1989
The normalized Kolmogorov-Smirnov and variational distance between the distribution of the sample q-quantile and the pertaining smooth bootstrap distribution are asymptotically distributed like the absolute value of a normal random variable. The distribution functions of these random distances may serve as measures of the accuracy of the bootstrap ...
Falk, M., Reiss, R.-D.
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Inference via kernel smoothing of bootstrap values

Computational Statistics & Data Analysis, 2007
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Jeffrey S. Racine, James G. MacKinnon
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A Note on the Smoothed Bootstrap

2003
In this paper we treat the smoothed bootstrap based on histogram induced empirical measure. We demonstrate the superiority of this type of bootstrap in a very general sense. Moreover, we show that this bootstrap can effectively estimate the bias inherent from the histogram density estimation.
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Histospline smoothing the Bayesian bootstrap

Biometrika, 1988
Summary: This paper describes a version of the Bayesian bootstrap that assigns random Dirichlet mass uniformly across statistically equivalent blocks. The method requires prior knowledge that the underlying distribution is continuous with known compact support.
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